1. Field of the Invention
This invention relates to systems, which as used herein may include apparatus and/or methods, for determining terrestrial position information, and to systems for navigating an autonomous vehicle.
2. Related Art
There is presently under development a terrestrial position determining system, referred to as the global positioning system (GPS), designated NAVSTAR by the U.S. Government. In this system, a multitude of orbiting satellites will be used to determine the terrestrial position of receivers on the Earth. In the planned system, there will be eight orbiting satellites in each of three sets of orbits, 21 satellites on line and three spares, for a total of 24 satellites. The three sets of orbits will have mutually orthogonal planes relative to the Earth. The orbits are neither polar orbits nor equatorial orbits, however. The satellites will be in 12-hour orbits. The position of each satellite at all times will be precisely known. The longitude, latitude, and altitude with respect to the center of the Earth, of a receiver at any point close to Earth at the time of transmission, will be calculated by determining the propagation time of transmissions from at least four of the satellites to the receiver. The more satellites used the better. A current constraint on the number of satellites is that the currently available receiver only has five channels.
Energy on a single carrier frequency from all of the satellites is transduced by the receiver at a point close to Earth. The satellites from which the energy originated are identified by modulating the carrier transmitted from each satellite with pseudorandom type signals. In one mode, referred to as the coarse/acquisition (C/A) mode, the pseudorandom signal is a gold code sequence having a chip rate of 1.023 MHz; there are 1,023 chips in each gold code sequence, such that the sequence is repeated once every millisecond (the chipping rate of a pseudorandom sequence is the rate at which the individual pulses in the sequence are derived and therefore is equal to the code repetition rate divided by the number of members in the code; one pulse of the noise code is referred to as a chip).
The 1.023 MHz gold code sequence chip rate enables the position of the receiver responsive to the signals transmitted from four of the satellites to be determined to an accuracy of approximately 60 to 300 meters.
There is a second mode, referred to as the precise or protected (P) mode, wherein pseudorandom codes with chip rates of 10.23 MHz are transmitted with sequences that are extremely long, so that the sequences repeat no more than once per week. In the P mode, the position of the receiver can be determined to an accuracy of approximately 16 to 30 meters. However, the P mode requires Government classified information about how the receiver is programed and is intended for use only by authorized receivers. Hence, civilian and/or military receivers that are apt to be obtained by unauthorized users are not responsive to the P mode.
To enable the receivers to separate the C/A signals received from the different satellites, the receiver includes a plurality of different locally derived gold code sources, each of which corresponds with the gold code sequence transmitted from one of the satellites in the field of the receiver. The locally derived and the transmitted gold code sequences are cross correlated with each other over one millisecond, gold code sequence intervals. The phase of the locally derived gold code sequences vary on a chip-by-chip basis, and then within a chip, until the maximum cross correlation function is obtained. Since the cross correlation for two gold code sequences having a length of 1,023 bits is approximately 16 times as great as the cross correlation function of any of the other combinations of gold code sequences, it is relatively easy to lock the locally derived gold code sequence onto the same gold code sequence that was transmitted by one of the satellites.
The gold code sequences from at least four of the satellites in the field of view of the receiver are separated in this manner by using a single channel that is sequentially responsive to each of the locally derived gold code sequences or by using parallel channels that are simultaneously responsive to the different gold code sequences. After four locally derived gold code sequences are locked in phase with the gold code sequences received from four satellites in the field of view of the receiver, the position of the receiver can be determined to an accuracy of approximately 60 to 300 meters.
The approximately 60 to 300 meter accuracy of GPS is determined by (1) the number of satellites transmitting signals to which the receiver is effectively responsive, (2) the variable amplitudes of the received signals, and (3) the magnitude of the cross correlation peaks between the received signals from the different satellites.
In response to reception of multiple pseudorange noise (PRN) signals, there is a common time interval for some of the codes to likely cause a degradation in time of arrival measurements of each received PRN due to the cross correlations between the received signals. The time of arrival measurement for each PRN is made by determining the time of a peak amplitude of the cross correlation between the received composite signal and a local gold code sequence that is identical to one of the transmitted PRN. When random noise is superimposed on a received PRN, increasing the averaging time of the cross correlation between the signal and a local PRN sequence decreases the average noise contribution to the time of arrival error. However, because the cross correlation errors between the received PRN's are periodic, increasing the averaging time increases both signal and the cross correlation value between the received PRN's alike and time of arrival errors are not reduced.
In addition to the GPS, it is known in the field to use inertial systems to obtain user position estimates. Such an inertial reference unit (IRU) obtains specific-force measurements from accelerometers in a reference coordinate frame which is stabilized by gyroscopes. An IRU may be of the laser or mechanical type. In an unaided inertial navigation system, the accelerometer measured specific force (corrected for the effects of the Earth's gravity) is integrated in a navigation equation to produce the user's position and velocity.
The IRU instrument measurements may be specified in a different rectangular coordinate frame than the reference navigation frame, depending on the platform implementation. The most commonly used reference navigation frame for near Earth navigation is the local-level frame (east-north-vertical). For a gimballed, local level-north seeking IRU, the gyros and accelerometers are mounted on a platform which is torqued to maintain the platform level and azimuth pointing to the north. For a gimballed, local-level azimuth-wander IRU, on the other hand, the platform is maintained level but is not torqued about the vertical axis.
In a strap down mechanization of the IRU, on the other hand, the accelerometers and gyros are directly mounted on the vehicle body. They measure the linear and angular motion of the vehicle relative to inertial space, expressed in vehicle coordinates. It is, therefore, necessary in a strap down mechanization, to first compute numerically the attitude of the vehicle to the referenced navigation frame, and then use the computed attitude to transform the accelerometer measurements into the reference frame. After the accelerometer data of a strap down IRU have been resolved into the reference frame, the solution of the IRU navigation equations is identical in both the gimballed and strap down implementation.
In the strap down IRU implementation, the attitude computations, required to resolve accelerometer measurements, are carried out at a high rate. They suffer from numerical errors because of the limited computer word size and throughput availability. These computation errors depend on the frequency response of the sensor loop, data rate, and resolution and magnitude of the sensor output at the sampling time. There are significant benefits to a strap down IRU mechanization over a gimballed platform implementation. The potential to realize size and cost reduction in the IRU makes consideration of strap down systems attractive for both military and commercial applications.
The IRU navigation performance is primarily limited by its sensor error sources. Uncertainties in gyro drift and accelerometers bias, scale factor and IRU alignment angles are some of the significant error sources which effect the accuracy of the inertial navigator. Typically, these error sources cause errors in the estimates of user position, velocity and attitude, which accumulate with time on a mission and are, to some extent, user dynamics dependent.
To support a requirement of very accurate navigation, high precision gyros and accelerometers are required, which increase the complexity and costs of the vehicle.
Rudimentary autonomous, meaning unmanned or machine controlled, vehicle navigation is also known in the field.
Systems exist which rely on vision based positioning. For instance, vision based positioning is used in the Martin Marietta Autonomous Land Vehicle, as described in "Obstacle Avoidance Perception Processing for the Autonomous Land Vehicle," by R. Terry Dunlay, IEEE, CH2555-1/88/0000/0912501.00, 1988. (See also "A Curvature-based Scheme for Improving Road Vehicle Guidance by computer Vision," by E. D. Dickmanns and A. Zapp, as reported at SPIE's Cambridge Symposium on optical and Optoelectronic Engineering, Oct. 26-31, 1986.)
Some of these vision based positioning systems may use fixed lines or markings on, for instance, a factory floor, to navigate from point to point. Others may involve complex pattern recognition hardware and software. Other systems may navigate by keeping track of their position relative to a known starting point by measuring the distance they have travelled and the direction from the starting point. These measuring type systems are known as "dead-reckoning" systems.
Such navigation systems suffer from numerous drawbacks and limitations. For instance, if the system cannot recognize where it is, looses track of where it has been, or miscalculates its starting point, it will become unable to accurately reach its goal. Because errors in position accumulate in such systems, they may require frequent, time consuming initializations. Such systems may require patterns and markers be placed along their route, which is also time consuming and costly, and limits their usefulness to small, controlled areas.